Does Competition Increase Economic Efficiency in Swedish County Councils?

The Swedish health care system is to a large extent publicly managed by 21 local county councils. During recent years there has been a movement were local county councils have opted to allow more of the production to be performed by alternative producers (i.e. private firms, cooperatives etc.). The purpose of this paper is thus to study if local county councils who has a large proportion of health care performed by alternative producers are more economically efficient than other county councils. The results indicate that county councils with more alternative caregivers are supplying their services more efficiently.Economic efficiency in health care; Data Envelopment Analysis; Tobit regression

Facilitated Assessment of Tissue Loss Following Traumatic Brain Injury

All experimental models of traumatic brain injury (TBI) result in a progressive loss of brain tissue. The extent of tissue loss reflects the injury severity and can be measured to evaluate the potential neuroprotective effect of experimental treatments. Quantitation of tissue volumes is commonly performed using evenly spaced brain sections stained using routine histochemical methods and digitally captured. The brain tissue areas are then measured and the corresponding volumes are calculated using the distance between the sections. Measurements of areas are usually performed using a general purpose image analysis software and the results are then transferred to another program for volume calculations. To facilitate the measurement of brain tissue loss we developed novel algorithms which automatically separate the areas of brain tissue from the surrounding image background and identify the ventricles. We implemented these new algorithms by creating a new computer program (SectionToVolume) which also has functions for image organization, image adjustments and volume calculations. We analyzed brain sections from mice subjected to severe focal TBI using both SectionToVolume and ImageJ, a commonly used image analysis program. The volume measurements made by the two programs were highly correlated and analysis using SectionToVolume required considerably less time. The inter-rater reliability was high. Given the extensive use of brain tissue loss measurements in TBI research, SectionToVolume will likely be a useful tool for TBI research. We therefore provide both the source code and the program as attachments to this article

Neurofilament light and tau as blood biomarkers for sports-related concussion

OBJECTIVE: To compare neurofilament light (NfL) and tau as blood-based biomarkers for acute sports-related concussion (SRC) and determine whether their concentrations at different time points after the injury are associated with prolonged time to return to play (RTP).METHODS: A total of 288 professional hockey players were followed longitudinally from September 1, 2012, to April 30, 2015. Data collection and biomarker analyses were conducted between 2015 and 2017. Associations were tested between blood concentrations of NfL and tau, and RTP time. Serum concentrations of S100B and neuron-specific enolase (NSE) were also measured for comparison.RESULTS: Of 288 players, 105 sustained an SRC. Of these, 87 underwent blood sampling 1, 12, 36, and 144 hours after SRC and at the RTP time point. Serum NfL concentrations 1, 12, 36, and 144 hours after SRC were related to prolonged RTP time, and could separate players with RTP >10 days from those with RTP ≤10 days (area under the receiver operating characteristic curve [AUROC] 0.82). Also, serum NfL 144 hours after SRC discriminated players who resigned from the game due to persistent postconcussion symptoms (PCS) from those who returned to play (AUROC 0.89). Plasma tau 1 hour after SRC was related to RTP but less strongly than NfL, while S100B and NSE showed no such associations.CONCLUSION: Serum NfL outperformed tau, S100B, and NSE as a biomarker for SRC. From a clinical standpoint, serum NfL may be useful to identify individuals at risk of prolonged PCS, and may aid in biomarker-informed decisions with regard to when RTP should be considered

"Omics" in traumatic brain injury: novel approaches to a complex disease

Background: To date, there is neither any pharmacological treatment with efficacy in traumatic brain injury (TBI) nor any method to halt the disease progress. This is due to an incomplete understanding of the vast complexity of the biological cascades and failure to appreciate the diversity of secondary injury mechanisms in TBI. In recent years, techniques for high-throughput characterization and quantification of biological molecules that include genomics, proteomics, and metabolomics have evolved and referred to as omics.Methods: In this narrative review, we highlight how omics technology can be applied to potentiate diagnostics and prognostication as well as to advance our understanding of injury mechanisms in TBI.Results: The omics platforms provide possibilities to study function, dynamics, and alterations of molecular pathways of normal and TBI disease states. Through advanced bioinformatics, large datasets of molecular information from small biological samples can be analyzed in detail and provide valuable knowledge of pathophysiological mechanisms, to include in prognostic modeling when connected to clinically relevant data. In such a complex disease as TBI, omics enables broad categories of studies from gene compositions associated with susceptibility to secondary injury or poor outcome, to potential alterations in metabolites following TBI.Conclusion: The field of omics in TBI research is rapidly evolving. The recent data and novel methods reviewed herein may form the basis for improved precision medicine approaches, development of pharmacological approaches, and individualization of therapeutic efforts by implementing mathematical "big data" predictive modeling in the near future.</p

Spatio-temporal analysis of prostate tumors in situ suggests pre-existence of treatment-resistant clones

The molecular mechanisms underlying lethal castration-resistant prostate cancer remain poorly understood, with intratumoral heterogeneity a likely contributing factor. To examine the temporal aspects of resistance, we analyze tumor heterogeneity in needle biopsies collected before and after treatment with androgen deprivation therapy. By doing so, we are able to couple clinical responsiveness and morphological information such as Gleason score to transcriptome-wide data. Our data-driven analysis of transcriptomes identifies several distinct intratumoral cell populations, characterized by their unique gene expression profiles. Certain cell populations present before treatment exhibit gene expression profiles that match those of resistant tumor cell clusters, present after treatment. We confirm that these clusters are resistant by the localization of active androgen receptors to the nuclei in cancer cells post-treatment. Our data also demonstrates that most stromal cells adjacent to resistant clusters do not express the androgen receptor, and we identify differentially expressed genes for these cells. Altogether, this study shows the potential to increase the power in predicting resistant tumors

Spatially resolved clonal copy number alterations in benign and malignant tissue

Publisher Copyright: © 2022, The Author(s).Defining the transition from benign to malignant tissue is fundamental to improving early diagnosis of cancer1. Here we use a systematic approach to study spatial genome integrity in situ and describe previously unidentified clonal relationships. We used spatially resolved transcriptomics2 to infer spatial copy number variations in >120,000 regions across multiple organs, in benign and malignant tissues. We demonstrate that genome-wide copy number variation reveals distinct clonal patterns within tumours and in nearby benign tissue using an organ-wide approach focused on the prostate. Our results suggest a model for how genomic instability arises in histologically benign tissue that may represent early events in cancer evolution. We highlight the power of capturing the molecular and spatial continuums in a tissue context and challenge the rationale for treatment paradigms, including focal therapy.Peer reviewe

Spatially resolved clonal copy number alterations in benign and malignant tissue

Publisher Copyright: © 2022, The Author(s).Defining the transition from benign to malignant tissue is fundamental to improving early diagnosis of cancer1. Here we use a systematic approach to study spatial genome integrity in situ and describe previously unidentified clonal relationships. We used spatially resolved transcriptomics2 to infer spatial copy number variations in >120,000 regions across multiple organs, in benign and malignant tissues. We demonstrate that genome-wide copy number variation reveals distinct clonal patterns within tumours and in nearby benign tissue using an organ-wide approach focused on the prostate. Our results suggest a model for how genomic instability arises in histologically benign tissue that may represent early events in cancer evolution. We highlight the power of capturing the molecular and spatial continuums in a tissue context and challenge the rationale for treatment paradigms, including focal therapy.Peer reviewe